Additive Pattern Database Heuristics

We explore a method for computing admissible heuristic evaluation functions for search problems. It utilizes pattern databases, which are precomputed tables of the exact cost of solving various subproblems of an existing problem. Unlike standard pattern database heuristics, however, we partition our problems into disjoint subproblems, so that the costs of solving the different subproblems can be added together without overestimating the cost of solving the original problem. Previously, we showed how to statically partition the sliding-tile puzzles into disjoint groups of tiles to compute an admissible heuristic, using the same partition for each state and problem instance. Here we extend the method and show that it applies to other domains as well. We also present another method for additive heuristics which we call dynamically partitioned pattern databases. Here we partition the problem into disjoint subproblems for each state of the search dynamically. We discuss the pros and cons of each of these methods and apply both methods to three different problem domains: the sliding-tile puzzles, the 4-peg Towers of Hanoi problem, and finding an optimal vertex cover of a graph. We find that in some problem domains, static partitioning is most effective, while in others dynamic partitioning is a better choice. In each of these problem domains, either statically partitioned or dynamically partitioned pattern database heuristics are the best known heuristics for the problem

Comparative Methods for Gene Structure Prediction in Homologous Sequences

The increasing number of sequenced genomes motivates the use of evolutionary patterns to detect genes. We present a series of comparative methods for gene finding in homologous prokaryotic or eukaryotic sequences. Based on a model of legal genes and a similarity measure between genes, we find the pair of legal genes of maximum similarity. We develop methods based on genes models and alignment based similarity measures of increasing complexity, which take into account many details of real gene structures, e.g. the similarity of the proteins encoded by the exons. When using a similarity measure based on an exiting alignment, the methods run in linear time. When integrating the alignment and prediction process which allows for more fine grained similarity measures, the methods run in quadratic time. We evaluate the methods in a series of experiments on synthetic and real sequence data, which show that all methods are competitive but that taking the similarity of the encoded proteins into account really boost the performance

Synthesis and Optimization of Reversible Circuits - A Survey

Reversible logic circuits have been historically motivated by theoretical research in low-power electronics as well as practical improvement of bit-manipulation transforms in cryptography and computer graphics. Recently, reversible circuits have attracted interest as components of quantum algorithms, as well as in photonic and nano-computing technologies where some switching devices offer no signal gain. Research in generating reversible logic distinguishes between circuit synthesis, post-synthesis optimization, and technology mapping. In this survey, we review algorithmic paradigms --- search-based, cycle-based, transformation-based, and BDD-based --- as well as specific algorithms for reversible synthesis, both exact and heuristic. We conclude the survey by outlining key open challenges in synthesis of reversible and quantum logic, as well as most common misconceptions.Comment: 34 pages, 15 figures, 2 table

Entropy-based analysis of the number partitioning problem

In this paper we apply the multicanonical method of statistical physics on the number-partitioning problem (NPP). This problem is a basic NP-hard problem from computer science, and can be formulated as a spin-glass problem. We compute the spectral degeneracy, which gives us information about the number of solutions for a given cost $E$ and cardinality $m$. We also study an extension of this problem for $Q$ partitions. We show that a fundamental difference on the spectral degeneracy of the generalized ($Q>2$) NPP exists, which could explain why it is so difficult to find good solutions for this case. The information obtained with the multicanonical method can be very useful on the construction of new algorithms.Comment: 6 pages, 4 figure

Analysis of the Karmarkar-Karp Differencing Algorithm

The Karmarkar-Karp differencing algorithm is the best known polynomial time heuristic for the number partitioning problem, fundamental in both theoretical computer science and statistical physics. We analyze the performance of the differencing algorithm on random instances by mapping it to a nonlinear rate equation. Our analysis reveals strong finite size effects that explain why the precise asymptotics of the differencing solution is hard to establish by simulations. The asymptotic series emerging from the rate equation satisfies all known bounds on the Karmarkar-Karp algorithm and projects a scaling $n^{-c\ln n}$, where $c=1/(2\ln2)=0.7213...$. Our calculations reveal subtle relations between the algorithm and Fibonacci-like sequences, and we establish an explicit identity to that effect.Comment: 9 pages, 8 figures; minor change

Untreated Type 2 Diabetes and Its Complications Are Associated With Subcortical Infarctions

OBJECTIVE - To investigate the association of type 2 diabetes with subcortical infarctions. RESEARCH DESIGN AND METHODS - We investigated this association in subjects with type 2 diabetes (case subjects; n = 93) and without type 2 diabetes (control subjects; n = 186), matched by age, sex, and years of education. Participants were a subset of the Mayo Clinic Study of Aging (median age 79 years) who had undergone magnetic resonance imaging. RESULTS - The frequency of subcortical infarctions was 39% in case subjects and 29% in control subjects (odds ratio 1.59 [95% CI 0.91-2.75]). The association was stronger in case subjects without treatment (2.60 [1.11- 6.08]) and in case subjects with diabetes-related complications (1.96 [1.02-3.74]) compared with control subjects. CONCLUSIONS - These findings suggest that untreated type 2 diabetes and type 2 diabetes with complications are associated with subcortical infarctions. © 2011 by the American Diabetes Association